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Mining time series data: Case of predicting consumption patterns in steel industry

机译:挖掘时间序列数据:预测钢铁行业消费模式的案例

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Analyzing and predicting with Time series is a method which used in different fields, including consumption pattern analyzing and predicting. In this paper, required amount of inventory items have been predicted with time series. At first, desired data mining process is designed and implemented using Clementine data mining tool. We evaluate this process using the dataset from Iran's ZoabAhan steel company. Results show that by using this process not only we can model consumption patterns for the present time but also we can predict required stock items for future with adequate accuracy.
机译:时间序列分析和预测是一种用于不同领域的方法,包括消费模式分析和预测。在本文中,已按时间序列预测了所需的库存项目数量。首先,使用Clementine数据挖掘工具设计和实现所需的数据挖掘过程。我们使用来自伊朗ZoabAhan钢铁公司的数据集评估此过程。结果表明,通过使用此过程,我们不仅可以对当前的消费模式进行建模,而且可以足够准确地预测未来所需的库存项目。

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